Restricted Boltzmann Machines (RBMs) [1]}, [2]} are probabilistic models that employ a layer of hidden binary units, also known as latent units, to model the distribution of the input data (visible layer). Such models have been applied to deal with problems involving images [3]}, text [4]}, detection of malicious content [5]}, [6]}, and several diseases diagnosis [7]}, [8]}, [9]}, just to cite a few. Moreover, RBMs are also used for building deep learning architectures, such as Deep Belief Networks (DBNs) [10]} and Deep Boltzmann Machine (DBM) [11]}, [12]}, where the main difference is related to the interaction among layers of RBMs.
